| 吕梁市农机总动力预测 |
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| 引用本文： | 张建勋.吕梁市农机总动力预测[J].农业工程,2020,10(5):21-23. |
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| 作者姓名： | 张建勋 |
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| 作者单位： | 吕梁市农业机械化技术推广站,山西 吕梁 033000 |
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| 摘 要： | 以1979—2015年吕梁市农机总动力为研究基础，利用指数函数、三次多项式函数及BP神经网络分别建立农机总动力预测模型并进行样本比对。结果表明，BP神经网络和指数函数模型的平均绝对误差分别为1.11%和3.22%，低于三次多项式函数的平均绝对误差（8.05%）。利用BP神经网络模型和指数函数模型对2016—2021年吕梁市农机总动力进行预测，以期为农业机械化水平的发展提供参考。
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| 关 键 词： | 农机总动力 预测 BP神经网络 |
| 收稿时间： | 2020/3/19 0:00:00 |
| 修稿时间： | 2020/3/19 0:00:00 |
Prediction for Total Power of Agricultural Machinery in Lvliang City |
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| ZHANG Jianxun.Prediction for Total Power of Agricultural Machinery in Lvliang City[J].Agricultural Engineering,2020,10(5):21-23. |
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| Authors: | ZHANG Jianxun |
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| Abstract: | Based on research of total power of agricultural machinery in Lvliang city from 1979 to 2015，the exponential function，the cubic polynomial function and the BP neural network were used to establish prediction model of total power of agricultural machinery and compare the samples.Results showed that average absolute errors of the BP neural network and the exponential function model were 1.11% and 3.22%，respectively，which were lower than average absolute error of the cubic polynomial function （8.05%）.Finally，the BP neural network model and the exponential function model were used to predict total power of agricultural machinery in Lvliang city in 2016—2021，with a view to providing a reference for development of agricultural mechanization level. |
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